The Accuracy of Physicians' Clinical Predictions of Survival in Patients With Advanced Cancer

Clinical Implications of the C-Reactive Protein-Albumin Ratio as a Prognostic Marker in Terminally Ill Patients with Cancer

Background: Few studies investigated the clinical implications of C-reactive protein-albumin ratio (CAR) in palliative care. Objectives: To determine the association of CAR with overall survival among terminally ill patients with cance. Design: Datasets were obtained through two multicenter prospective cohort studies. Setting/Subjects: Patients newly referred to palliative care. Measurements: Physicians recorded measures at the baseline. Patients were followed up to their death or observed for 6 months. The patients in cohort 2 were divided using the CAR cutoffs detected using a piecewise linear hazards model in cohort 1. We performed time-to-event analyses using the Kaplan-Meier method and log-rank tests and univariate and multivariate Cox regression analyses for patients in cohort 2. Results: A total of 1554 patients in cohort 1 and 1517 patients in cohort 2 were eligible. The cutoffs were 0.1, 1.2, and 6.4. The patients in cohort 2 were divided into four categories (<0.1 [n = 103], 0.1-1.2 [n = 433], 1.2-6.4 [712], and ≥6.4 [n = 269]). The adjusted p values of the log-rank tests were <0.001. Significantly higher risks of mortality were observed in the Cox proportional hazard model for the higher categories than in the lowest category (CAR 0.1-1.2: adjusted hazard ratio [HR] 1.49, 95% confidence interval [CI] 1.18-1.89; CAR 1.2-6.4: adjusted HR 2.08, 95% CI 1.65-2.62; CAR ≥6.4: adjusted HR 2.94, 95% CI 2.29-3.79). Conclusions: Patients with a higher CAR had significantly higher risks of mortality than those with a lower CAR.

Accuracy of Medical Oncology Prognosis for Metastatic Cancer Patients Evaluated for Enrollment Onto an Ongoing Randomized Clinical Trial

OBJECTIVES

For patients with metastatic cancer, a key aspect of interdisciplinary care has involved the overall prognosis provided by Medical Oncology. This study represents prospective evaluation of Medical Oncology prognosis accuracy for patients considered for enrollment onto an ongoing randomized controlled trial.

METHODS

The Spine Patient Optimal Radiosurgery Treatment for Symptomatic Metastatic Neoplasms (SPORTSMEN) phase 2 randomized clinical trial examines optimal radiation therapy treatment of symptomatic spinal metastases with a primary end point of pain freedom at 3 months post-treatment. A key eligibility criterion for trial enrollment is overall prognosis exceeding 3 months, typically provided by Medical Oncology. During the first year of trial enrollment, Medical Oncology prognosis for patients considered for SPORTSMEN inclusion was prospectively assessed for accuracy.

RESULTS

Twenty-seven patients with documented Medical Oncology prognosis were considered for SPORTSMEN enrollment. The prognosis administered by Medical Oncology exceeded 3 months in 26 patients, and <3 months in 1 patient. The overall accuracy of Medical Oncology prognosis was correct for 15 of 27 patients (56%), significantly worse for inpatients than outpatients ( P =0.0381).

CONCLUSIONS

In patients with metastatic spine disease, the estimated prognosis provided by Medical Oncology is often optimistic, as nearly half of patients assigned a prognosis of >3 months failed to reach this threshold before experiencing death or hospice. These findings indicate that a more heuristic approach to assessing patient prognosis may be necessary to avoid unwarranted prognostic optimism, particularly for inpatients. Such an approach could potentially provide a more compassionate and cost-effective management of these patients' remaining lifespan thereby optimizing quality of life.

Comparison of Prognostic Abilities of Palliative Prognostic Index, Laboratory Prognostic Score, and Palliative Prognostic Score

CONTEXT

Few studies have compared the prognostic value of scoring systems based on physical and blood parameters in terminally ill patients with cancer.

OBJECTIVES

This study evaluated the prognostic abilities of Palliative Prognostic Index (PPI), Laboratory Prognostic Score (LPS), and Palliative Prognostic Score (PaP).

METHODS

We included 989 terminally ill patients with cancer who consulted for admission to our palliative care unit. We compared the discriminative abilities of PPI, LPS, and PaP for 7-, 14-, 30-, 60-, and 90-day mortality. Additionally, we compared the estimated median survival of PPI, LPS, and PaP with the actual survival (AS). The prediction accuracy was considered adequate if the ratio of estimated median survival in days to AS in days fell within the range of 0.66 to 1.33, optimistic when it exceeds 1.33, and pessimistic when it falls below 0.66.

RESULTS

The accuracies for 7-, 14-, 30-, 60-, and 90-day mortality were superior for PPI, LPS, LPS, PaP, and PaP (72%, 73%, 71%, 80%, and 82%), respectively, although the discriminative abilities for 7-, 14-, 30-, 60-, and 90-day mortality were similar among the three scoring systems. The prediction accuracy of survival (PAS) was similar among the three scoring systems with adequate, optimistic, and pessimistic rates of 36%-41%, 20%-46%, and 16%-38%, respectively. PAS was superior in actual survival for 14-59 days.

CONCLUSIONS

The prognostic abilities of PPI, LPS, and PaP were comparable. The most adequate estimation occurred for patients with AS for 14-59 days. A more accurate prognostic model is needed for patients with longer survival.

Factors related to accurate clinicians' prediction of survival: an international multicenter study in East Asia

PURPOSE

Recent guidelines for prognostic evaluation recommend clinicians' prediction of survival (CPS) for survival prediction in patients with advanced cancer. However, CPS is often inaccurate and optimistic. Studies on factors associated with overestimation or underestimation of CPS are limited. We aimed to investigate the factors associated with the overestimation and underestimation of CPS in patients with far-advanced cancer.

METHODS

The current study was a secondary analysis of an international multicenter prospective cohort study, which enrolled newly admitted patients with advanced cancer in palliative care units (PCUs) in Japan, Korea, and Taiwan from 2017 to 2018. We obtained the temporal CPS at enrollment and performed multivariate logistic regression analysis to identify the factors associated with "underestimation (less than 33% of actual survival)" and "overestimation (more than 33% of actual survival)."

RESULTS

A total of 2571 patients were assessed and admitted in 37 PCUs between January 2017 and September 2018. Older age (adjusted odds ratio [aOR] 1.01; 95% confidence interval [CI] 1.01-1.02; P < 0.01) and reduced oral intake (aOR 0.68; 95% CI 0.51-0.89; P < 0.01) were identified as significant factors associated with underestimation. Dyspnea (aOR 1.28; 95% CI 1.06-1.54; P = 0.01) and hyperactive delirium (aOR 1.34; 95% CI 1.05-1.72; P = 0.02) were identified as significant factors associated with overestimation.

CONCLUSION

Older age was related to underestimation, while dyspnea and hyperactive delirium were related to overestimation of CPS for patients with weeks of survival. However, reduced oral intake was less likely to lead to underestimation.

How accurate is clinical prognostication by oncologists during routine practice in a general hospital and can it be improved by a specific prognosis training programme: a prospective interventional study

OBJECTIVES

Oncologists need competence in clinical prognostication to deliver appropriate care to patients with cancer. Most studies on prognostication have been restricted to patients in palliative care settings. This paper investigates (1) the prognostic accuracy of physicians regarding a broad cohort of patients with cancer with a median life expectancy of >2 years and (2) whether a prognosis training can improve prognostication.

DESIGN

Prospective single-centre study comprising 3 phases, each lasting 1 month.

SETTING

Large teaching hospital, department of oncology and haematology, Germany.

PARTICIPANTS

18 physicians with a professional experience from entry level to 34 years. 736 patients with oncological and malignant haematological diseases.

INTERVENTIONS

Baseline prognostication abilities were recorded during an 'untrained' phase 1. As an intervention, a specific prognosis-training programme was implemented prior to phases 2 and 3. In phase 3, physicians had to provide additional estimates with the inclusion of electronic prognostic tools.

OUTCOME MEASURES

Prognostic estimates (PE) were collected using 'standard' surprise question (SQ), 'probabilistic' SQ (both for short-term prognostication up to 6 months) and clinician prediction of survival (CPS) (for long-term prognostication). Estimated prognoses were compared with observed survival. Phase 1 was compared with phases 2 and 3.

RESULTS

We included 2427 PE for SQ, 1506 for CPS and 800 for probabilistic SQ. Median OS was 2.5 years. SQ accuracy improved significantly (p<0.001) from 72.6% in phase 1 to 84.3% in phase 3. Probabilistic SQ in phase 3 showed 83.1% accuracy. CPS accuracy was 25.9% and could not be significantly improved. (Electronic) prognostic tools-used alone-performed significantly worse (p<0.0005) than physicians and-used by the clinicians-did not improve their performance.

CONCLUSION

A specific prognosis-training programme could improve short-term and intermediate-term prognostication. Improvement of long-term prognostication was not possible. Inexperienced residents as well as experienced oncologists benefited from training.

Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides

Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study.

Anticancer therapy at end-of-life: A retrospective cohort study

BACKGROUND

A significant proportion of patients with incurable cancer receive systemic anticancer therapy (SACT) within their last 30 days of life (DOL). The treatment has questionable benefit, nevertheless is considered a quality indicator of end-of-life (EOL) care. This retrospective cohort study aims to investigate the rates and potential predictors of SACT and factors associated with SACT within the last 30 DOL. The study also evaluates the scope of Eastern Cooperative Oncology Group (ECOG) performance status and the modified Glasgow prognostic score (mGPS) as decision-making tools for oncologists.

PATIENTS AND MATERIAL

This review of medical records included 383 patients with non-curable cancer who died between July 2018 and December 2019. Descriptive statistics with Chi-squared tests and regression analysis were used to identify factors associated with SACT within the last 30 DOL.

RESULTS

Fifty-seven (15%) patients received SACT within the last 30 DOL. SACT within 30 last DOL was associated with shorter time from diagnosis until death (median 234 days vs. 482, p = 0.008) and ECOG score < 3 30 days prior to death (p = 0.001). Patients receiving SACT during the last 30 DOL were more likely to be hospitalised and die in hospital. ECOG and mGPS score were stated at start last line of treatment only in 139 (51%) and 135 (49%) respectively.

INTERPRETATION

Those with short time since diagnosis tended to receive SACT more frequently the last 30 DOL. The use of mGPS as a decision-making tool is modest, and there is lack in documentation of performance status.

Are Surprise Questions and Probabilistic Questions by Nurses Useful in Home Palliative Care? A Prospective Study

Background: Surprise questions (SQs) are used as screening tools in palliative care. Probabilistic questions (PQs) are more accurate than temporal predictions. However, no study has examined the usefulness of SQs and PQs assessed by nurses. Objectives: To examine the accuracy of nurses' SQ and PQ assessments in patients with advanced cancer receiving home palliative care. Design: A prospective single-center cohort study. Setting/Subjects: Adult patients with advanced cancer who received palliative care at home in South Korea between 2019 and 2020. Measurements: Palliative care specialized nurses were asked the SQ, "Would you be surprised if the patient died in a specific timeframe?" and PQ, "What is the probability that this patient will be alive (0 to 100%) within a specific timeframe?" at the 1-, 2-, 4-, and 6-week timeframes at enrollment. We calculated the sensitivities and specificities of the SQs and PQs. Results: 81 patients were recruited with 47 days of median survival. The sensitivity, specificity, and overall accuracy (OA) of the 1-week SQ were 50.0, 93.2, and 88.9%, respectively. The accuracies for the 1-week PQ were 12.5, 100.0, and 91.3%, respectively. The 6-week SQ showed sensitivity, specificity, and OA of 84.6, 42.9, and 62.9%, respectively; the accuracies for the 6-week PQ were 59.0, 66.7, and 63.0%, respectively.Conclusion: The SQ and PQ showed acceptable accuracy in home palliative care patients. Interestingly, PQ showed higher specificity than SQ at all timeframes. The SQ and PQ assessed by nurses may be useful in providing additional prognostic information for home palliative care.

Usefulness of the Palliative Prognostic Index in Predicting Prognosis when Considering the Transition from Hospital to Home Care in Patients with Terminal Stage Cancer

BACKGROUND

No accurate prognostic tool is available for patients with cancer who spend their final days at home. In this study, we examined whether performance status (PS) and the palliative prognostic index (PPI), a well-known prognostic tool in palliative care units, could be used to predict prognosis in the home care setting at the time of intervention by home physicians.

SUBJECTS AND METHODS

Using medical records, we conducted a retrospective analysis of 132 patients who were referred to the Home Clinic Naginoki for home care for terminal stages of carcinoma in situ. Based on the status at the time of the first visit, the PPI-Low group was defined as those scoring six or below and the PPI-High group as those scoring greater than six.

RESULTS

The PPI-high group had a significantly poorer prognosis within 21 days than the PPI-low group (21-day-OS; Low 71.4% vs. High 13.2%; p<0.001). The Eastern Cooperative Oncology Group (ECOG) PS alone predicted better prognosis in the group with PS of one or two (21-day survival 90.1%), and the PPI score further significantly stratified the prognosis for patients with PS three or four, with a trend toward poor prognosis (p ≤ 0.005).

CONCLUSION

ECOG PS 1 or 2 has a favorable prognosis and that using PPI in ECOG PS 3 or 4 leads to a more accurate prognosis prediction. PPI evaluated during the hospital-based treatment of patients with terminal cancer can also be used to predict prognosis if the patient is transitioned to a home care environment.

Muscle mass cross-sectional area is associated with survival outcomes in malignant pleural disease related to lung cancer

INTRODUCTION

Malignant pleural effusions are common in advanced malignancy and associated with overall poor survival. The presence of sarcopenia (decreased muscle mass) is associated with poor outcomes in numerous disease states, however, its relationship to malignant pleural disease has not been defined. We sought to understand if there was an association between decreased survival and decreased muscle mass in patients with malignant pleural effusion.

METHODS

Patients with malignant pleural disease undergoing indwelling tunneled pleural catheter placement were retrospectively reviewed. Computed tomography was reviewed and cross-sectional area of pectoralis and paraspinous muscle areas were calculated. Overall survival and associations with muscle mass were calculated.

RESULTS

A total of 309 patients were available for analysis, with a median age of 67 years and the majority female (58%). The median survival was 129 days from initial pleural drainage to death. Regression analysis and Kaplan-Meier survival analysis did not reveal an association with survival and muscle mass for the entire population. However, Kaplan-Meier survival analysis of the lung cancer subgroup revealed the presence of decreased muscle mass and decreased survival time.

CONCLUSION

The presence of decreased muscle mass within a lung cancer population that has malignant pleural effusions are associated with decreased survival. However, the presence of decreased muscle mass within a heterogenous population of malignant pleural disease was not associated with decreased overall survival time. Further study of the role that sarcopenia may play in malignant pleural disease is warranted.

Aggressiveness of Cancer Care at End of Life in Patients with Metastatic Breast Cancer in Jordan

Background

Contrary to Western societies, more than 15% of patients with breast cancer in Jordan are diagnosed with stage IV disease. In this study, we evaluate the value of early palliative care integration in the end-of-life care of such patients.

Methods

All consecutive adult patients who died between 2014 to 2018, while under the care of our institution, with a confirmed diagnosis of breast cancer at the time of death, irrespective of place of death, were retrospectively reviewed.

Results

During the study period, a total of 433 patients, median age 51.6 years, were included in the analysis. Among the whole group, 102 (23.6%) were referred to palliative care service early (≥30 days prior to death), 182 (42.0%) had late referral (<30 days from death), while 149 (34.4%) were never referred and were followed up by their medical oncologists. During the last 30 days prior to death, patients who were never referred to palliative care were more likely to visit the Emergency Room (ER) more than once (OR 1.89, 95% CI 1.20-2.99, p = 0.006), more likely to be admitted to the hospital more than once (OR 2.27, 95% CI 1.38-3.73, p = 0.001), and more likely to be admitted to the intensive care unit (ICU) (OR 3.07, 95% CI 1.48-6.38, p = 0.0027). Fewer patients in the "no referral" group died with advance directives compared to those who had early or late referral; 60.8%, 75.0% and 82.5%, respectively, p = 0.0003. Survival of patients followed by medical oncologist was not better than those referred to palliative care, either late or early; median survival was 19.0, 19.1 and 23.8 months, respectively (p = 0.2338).

Conclusion

Findings suggest that earlier palliative care referral is associated with less aggressive end-of-life care, leading to less frequent ER visits, hospital and ICU admissions during the last month of life, and does not compromise survival.

Use and safety of peripherally inserted central catheters and midline catheters in palliative care cancer patients: a retrospective review

PURPOSE

Some cancer patients in palliative care require intravenous administration of symptom relieving drugs. Peripherally inserted central catheters (PICCs) and midline catheters (MCs) provide easy and accessible intravenous access. However, limited evidence supports the use of these devices in palliative care. The aim was to assess the use, safety, and efficacy of PICC and MC in this patient population.

METHODS

A retrospective study of all palliative care cancer patients who received PICC or MC at the Department of Palliative Medicine at Akershus University Hospital between 2020 and 2022.

RESULTS

A total of 374 patients were included; 239 patients received a PICC and 135 an MC with a total catheterization duration of 11,698 days. The catheters remained in place until death in 91% of patients, with a median catheter dwell time of 21 days for PICCs and 2 days for MCs. The complication rate was 3.3 per 1000 catheter days, with minor bleeding and accidental dislocation as the most common. The catheters were utilized primarily for opioids and other symptom directed treatments, and 89% of patients received a patient or nurse-controlled analgesia pump. Patients with PICC or MC discharged to home or nursing homes spent 81% of their time out of hospital.

CONCLUSION

PICC and MC provide safe parenteral access for palliative care cancer patients where intravenous symptom treatment is indicated. Their use can facilitate intravenous symptom treatment beyond the confines of a hospital and supplement the traditional practice relying on subcutaneous administration.

Validation of Modified Models of Objective Prognostic Score in Patients With Advanced Cancer

Background: The objective prognostic score (OPS) needs to be modified to reflect practical palliative care circumstances. Objectives: We aimed to validate modified models of OPS with few or no laboratory tests for patients with advanced cancer. Design: An observational study was performed. Setting/Subjects: A secondary analysis of an international, multicenter cohort study of patients in East Asia was performed. The subjects were inpatients with advanced cancer in the palliative care unit. Measurements: We developed two modified OPS (mOPS) models to predict two-week survival: mOPS-A consisted of two symptoms, two objective signs, and three laboratory results, while mOPS-B consisted of three symptoms, two signs, and no laboratory data. We compared the accuracy of the prognostic models using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Calibration plots for two-week survival and net reclassification indices (NRIs) were compared for the two models. Survival differences between higher and lower score groups of each model were identified by the log-rank test. Results: We included a total of 1796 subjects having median survival of 19.0 days. We found that mOPS-A had higher specificity (0.805-0.836) and higher AUROCs (0.791-0.797). In contrast, mOPS-B showed higher sensitivity (0.721-0.725) and acceptable AUROCs (0.740-0.751) for prediction of two-week survival. Two mOPSs showed good concordance in calibration plots. Considering NRIs, replacing the original OPS with mOPSs improved overall reclassification (absolute NRI: 0.47-4.15%). Higher score groups of mOPS-A and mOPS-B showed poorer survival than those of lower score groups (p < 0.001). Conclusions: mOPSs used reduced laboratory data and had relatively good accuracy for predicting survival in advanced cancer patients receiving palliative care.

Prediction Accuracy Between Terminally Ill Patients' Survival Length and the Estimations Made From Different Medical Staff, a Prospective Cohort Study

Background: Previous reports suggested the clinical predictions of survival (CPS) and prognostic scores had similar accuracy in patients with days to weeks of life. Objective: We aimed to evaluate and compare the accuracy of CPS by attending physicians, residents, and nurses in an acute palliative care unit at a medical center. Methods: This was a 1-year prospective cohort study. Survival prediction was made within 3 days after patients' admission and re-evaluated every week until patients' discharge or death. Associated factors of accurate survival predictions were also explored by multivariate logistic regression. Results: A total of 179 inpatients were recruited and 115 of them were included in this analysis. The mean age of participants was 72.9 years and the average length of actual survival was 11.5 ± 12.0 days. For patients with survival within 30 days, the medical staff tended to overestimate their life span. The predictions made by physicians and nurses showed much closer to actual survival length through repeated estimations. Patients with metastatic cancer (odds ratio: OR 2.77, 95% CI 1.23-6.22) or cognitive impairment (OR 2.39, 95% CI 1.12-5.11) had higher associations with accurate CPS. Poor performance status of ECOG (OR 1.82, 95% CI 1.09-3.02) and dysphagia (OR 2.01, 95% CI 1.07-3.77) were significant predictors for accurate CPS in patients with the survival of less than 2 weeks. Conclusions: The accuracy of CPS between different medical staff did not reveal significant differences in the study. The importance of re-evaluation for patients' survival length in clinical practice is worthy of attention.

Clinicians' Prediction of Survival and Prognostic Confidence in Patients with Advanced Cancer in Three East Asian Countries

Background: Little is known about accuracy and confidence of clinicians' prediction of survival (CPS) in East-Asian countries. Objective: We aimed to examine accuracy of CPS for 7-, 21-, and 42-day survival in palliative inpatients and its association with prognostic confidence. Design: An international prospective cohort study in Japan (JP), Korea (KR), and Taiwan (TW). Setting/Subjects: Subjects were inpatients with advanced cancer admitted to 37 palliative care units in three countries. Measurements: Discrimination of CPS was investigated through sensitivity, specificity, overall accuracy, and area under the receiver operating characteristics curves (AUROCs) according to 7-, 21-, and 42-day survival. The accuracies of CPS were compared with those of Performance Status-based Palliative Prognostic Index (PS-PPI). Clinicians were instructed to rate confidence level on a 0-10-point scale. Results: A total of 2571 patients were analyzed. The specificity was highest at 93.2-100.0% for the 7-day CPS, and sensitivity was highest at 71.5-86.8% for the 42-day CPS. The AUROCs of the seven-day CPS were 0.88, 0.94, and 0.89, while those of PS-PPI were 0.77, 0.69, and 0.69 for JP, KR, and TW, respectively. As for 42-day prediction, sensitivities of PS-PPI were higher than those of CPS. Clinicians' confidence was strongly associated with the accuracy of prediction in all three countries (all p-values <0.01). Conclusions: CPS accuracies were highest (0.88-0.94) for the seven-day survival prediction. CPS was more accurate than PS-PPI in all timeframe prediction except 42-day prediction in KR. Prognostic confidence was significantly associated with the accuracy of CPS.

Prediction of Survival Time in Advanced Lung Cancer: A Retrospective Study in Home-Based Palliative Care Unit

Background: There is a large group of patients suffering from lung cancer and receiving home hospice care in China. However, little is known about the prediction of their survival time. The purpose of this study was to determine whether quality of life independently predicts survival among advanced lung cancer survivors who are receiving home-based palliative care. Methods: In this retrospective study, we analyzed data from 937 advanced lung cancer patients who had received home-based palliative care between March 2010 and March 2020. We used Kaplan-Meier survival curves to determine the factors associated with survival time and applied the Cox proportional hazards model to examine the effect of quality of life on survival. Results: The study included 928 patients with a mean age of 63 years; and 72.1% of them were men. Factors associated with shortened survival included age, sex, place of residence, weight loss, anorexia, nausea, edema, quality of life, and Karnofsky performance status. After adjusting for other variables in a multivariate Cox proportional hazards model, we found that quality of life was an independent positive predictor of survival. Conclusions: As an independent factor predicting the survival of advanced lung cancer patients, quality of life should be taken seriously. Medical staff and healthcare workers need to pay special attention to this predictive factor since it may serve as early risk identification indicator for professionals who provide home-based palliative care, helping them to create effective personalized care plans.

Demystifying Prognosis : Understanding the Science and Art of Prognostication

The science of prognostication is emerging as a vital part of providing goal concordant patient care. Historically, modern medicine has tended to shy away from approaching prognostication as a core clinical skill, and prognosis as something to be shared directly with the patient. In recent years however, the medical field's shift towards a focus on patient autonomy and more openness in matters regarding end of life has propelled the study of prognostication into a more essential component of patient centered care. This calls for more emphasis on teaching the science of prognosis and the skill of prognostication as a core part of modern medical education. The following chapter aims to delve into the science of prognostication, explore the methods of formulating a prognosis, and discuss issues surrounding the communication of prognosis.

Are Prognostic Scores Better Than Clinician Judgment? A Prospective Study Using Three Models

CONTEXT

Several prognostic models such as the Palliative Performance Scale (PPS), Palliative Prognostic Index (PPI), Palliative Prognostic Score (PaP) have been developed to complement clinician's prediction of survival (CPS). However, few studies with large scales have been conducted to show which prognostic tool had better performance than CPS in patients with weeks of survival.

OBJECTIVES

We aimed to compare the prognostic performance of the PPS, PPI, PaP, and CPS in inpatients admitted to palliative care units (PCUs).

METHODS

This study was part of a multi-center prospective observational study involving patients admitted to PCUs in Japan. We computed their prognostic performance using the area under the receiver operating characteristics curve (AUROC) and calibration plots for seven, 14-, 30- and 60-day survival.

RESULTS

We included 1896 patients with a median overall survival of 19 days. The AUROC was 73% to 84% for 60-day and 30-day survival, 75% to 84% for 14-day survival, and 80% to 87% for seven-day survival. The calibration plot demonstrated satisfactory agreement between the observational and predictive probability for the four indices in all timeframes. Therefore, all four prognostic indices showed good performance. CPS and PaP consistently had significantly better performance than the PPS and PPI from one-week to two-month timeframes.

CONCLUSION

The PPS, PPI, PaP, and CPS had relatively good performance in patients admitted to PCUs with weeks of survival. CPS and PaP had significantly better performance than the PPS and PPI. CPS may be sufficient for experienced clinicians while PPS may help to improve prognostic confidence for inexperienced clinicians.

Comparison of Objective Prognostic Score and Palliative Prognostic Score performance in inpatients with advanced cancer in Japan and Korea

OBJECTIVE

Accurate prognostication is important for patients and their families to prepare for the end of life. Objective Prognostic Score (OPS) is an easy-to-use tool that does not require the clinicians' prediction of survival (CPS), whereas Palliative Prognostic Score (PaP) needs CPS. Thus, inexperienced clinicians may hesitate to use PaP. We aimed to evaluate the accuracy of OPS compared with PaP in inpatients in palliative care units (PCUs) in three East Asian countries.

METHOD

This study was a secondary analysis of a cross-cultural, multicenter cohort study. We enrolled inpatients with far-advanced cancer in PCUs in Japan, Korea, and Taiwan from 2017 to 2018. We calculated the area under the receiver operating characteristics (AUROC) curve to compare the accuracy of OPS and PaP.

RESULTS

A total of 1,628 inpatients in 33 PCUs in Japan and Korea were analyzed. OPS and PaP were calculated in 71.7% of the Japanese patients and 80.0% of the Korean patients. In Taiwan, PaP was calculated for 81.6% of the patients. The AUROC for 3-week survival was 0.74 for OPS in Japan, 0.68 for OPS in Korea, 0.80 for PaP in Japan, and 0.73 for PaP in Korea. The AUROC for 30-day survival was 0.70 for OPS in Japan, 0.71 for OPS in Korea, 0.79 for PaP in Japan, and 0.74 for PaP in Korea.

SIGNIFICANCE OF RESULTS

Both OPS and PaP showed good performance in Japan and Korea. Compared with PaP, OPS could be more useful for inexperienced physicians who hesitate to estimate CPS.

Prospective Comparison of Medical Oncologists and a Machine Learning Model to Predict 3-Month Mortality in Patients With Metastatic Solid Tumors

Importance

To date, oncologist and model prognostic performance have been assessed independently and mostly retrospectively; however, how model prognostic performance compares with oncologist prognostic performance prospectively remains unknown.

Objective

To compare oncologist performance with a model in predicting 3-month mortality for patients with metastatic solid tumors in an outpatient setting.

Design, Setting, and Participants

This prognostic study evaluated prospective predictions for a cohort of patients with metastatic solid tumors seen in outpatient oncology clinics at a National Cancer Institute-designated cancer center and associated satellites between December 6, 2019, and August 6, 2021. Oncologists (57 physicians and 17 advanced practice clinicians) answered a 3-month surprise question (3MSQ) within clinical pathways. A model was trained with electronic health record data from January 1, 2013, to April 24, 2019, to identify patients at high risk of 3-month mortality and deployed silently in October 2019. Analysis was limited to oncologist prognostications with a model prediction within the preceding 30 days.

Exposures

Three-month surprise question and gradient-boosting binary classifier.

Main Outcomes and Measures

The primary outcome was performance comparison between oncologists and the model to predict 3-month mortality. The primary performance metric was the positive predictive value (PPV) at the sensitivity achieved by the medical oncologists with their 3MSQ answers.

Results

A total of 74 oncologists answered 3099 3MSQs for 2041 patients with advanced cancer (median age, 62.6 [range, 18-96] years; 1271 women [62.3%]). In this cohort with a 15% prevalence of 3-month mortality and 30% sensitivity for both oncologists and the model, the PPV of oncologists was 34.8% (95% CI, 30.1%-39.5%) and the PPV of the model was 60.0% (95% CI, 53.6%-66.3%). Area under the receiver operating characteristic curve for the model was 81.2% (95% CI, 79.1%-83.3%). The model significantly outperformed the oncologists in short-term mortality.

Conclusions and Relevance

In this prognostic study, the model outperformed oncologists overall and within the breast and gastrointestinal cancer cohorts in predicting 3-month mortality for patients with advanced cancer. These findings suggest that further studies may be useful to examine how model predictions could improve oncologists' prognostic confidence and patient-centered goal-concordant care at the end of life.

Performance of clinician prediction of survival in oncology outpatients with advanced cancer

Background

We aimed to investigate the performance of clinician prediction of survival (CPS) and the association between CPS and the prognostic confidence of clinicians in ambulatory medical oncology outpatients.

Methods

Eight medical oncologists estimated the expected survival of their patients in a prospective cohort study. They were asked to provide a temporal type of CPS in weeks, together with their level of confidence for each prediction (0–100%). We analyzed the accuracy of CPS, the association between CPS and the prognostic confidence, and the characteristics of patients showing inaccurate CPS.

Results

A total of 200 advanced cancer patients were enrolled and the median overall survival was 7.6 months. CPS was accurate in 67 (33.5%) patients, underestimated in 87 (43.5%), and overestimated in 46 (23.0%). The overall accuracy of CPS for 12-week, 24-week, 36-week, and 48-week survival was 83.0%, 72.0%, 75.5%, and 74.0%, respectively. The specificity was highest for 12-week survival (90.2%) and the sensitivity was highest for 48-week survival (96.1%). The sensitivity of 12-week CPS was 51.4% and the area under the receiver operating characteristic (AUROC) curve was 0.79 (95% confidence interval [CI] 0.71–0.87). The prognostic confidence of clinicians was not significantly associated with the accuracy of prediction (P = 0.359). Patients with overestimated survival had significantly poorer global health status and physical/role/emotional functioning in the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). Additionally, they showed significantly higher levels of fatigue, nausea/vomiting, pain, dyspnea, and loss of appetite.

Conclusion

The overall accuracy of CPS in predicting 12-week to 48-week survival was high in medical oncology outpatients. However the sensitivity of 12-week CPS was low and prognostic confidence was not associated with the accuracy of CPS. Patients with overestimated CPS showed poorer quality of life and higher symptom burden.

Prognostication of the last days of life: Review article

Accurate prediction of impending death (i.e., last few days of life) is essential for terminally-ill cancer patients and their families. International guidelines state that clinicians should identify patients with impending death, communicate the prognosis with patients and families, help them with their end-of-life decision-making, and provide sufficient symptom palliation. Over the past decade, several national and international studies have been conducted that systematically investigated signs and symptoms of impending death as well as how to communicate such a prognosis effectively with patients and families. In this article, we summarize the current evidence on prognostication and communication regarding the last days of life of patients with cancer, and future directions of clinical research.

Incurable but treatable: Understanding, uncertainty and impact in chronic blood cancers-A qualitative study from the UK's Haematological Malignancy Research Network

Objective

Most blood cancers are incurable and typically follow unpredictable remitting-relapsing pathways associated with varying need for treatment, which may be distressing for patients. Our objective was to conduct a qualitative study to explore understanding among patients with such malignancies, including the explanations given by HCPs and the impact of uncertain trajectories, to generate evidence that could guide improvements in clinical practice.

Methods

The study is set within a population-based patient cohort (the Haematological Malignancy Research Network), in which care is delivered across 14 hospitals according to national guidelines. In-depth interviews were conducted with 35 patients with chronic lymphocytic leukaemia, follicular lymphoma, marginal zone lymphoma or myeloma; and 10 accompanying relatives. Purposive sampling ensured selection of information-rich participants and the data were interrogated using reflective thematic analysis.

Results

Rich data were collected and four themes (11 sub-themes) were identified: 1) Knowledge and understanding of chronic haematological malignancies; 2) Incurable but treatable; 3) Uncertainty about the future; and 4) Treatable (but still incurable): Impact on patients. Patients had rarely heard of blood cancer and many expressed difficulty understanding how an incurable malignancy that could not be removed, was treatable, often for long periods. While some were reassured that their cancer did not pose an immediate survival threat, others were particularly traumatised by the uncertain future it entailed, suffering ongoing emotional distress as a result, which could be more burdensome than any physical symptoms. Nonetheless, most interviewees understood that uncertain pathways were caused by the unpredictability of their disease trajectory, and not information being withheld.

Conclusions

Many participants lacked knowledge about chronic haematological malignancies. HCPs acted to reassure patients about their diagnosis, and while this was appropriate and effective for some, it was less so for others, as the cancer-impact involved struggling to cope with ongoing uncertainty, distress and a shortened life-span.

Comparison of the accuracy of clinicians' prediction of survival and Palliative Prognostic Score: an East Asian cross-cultural study

PURPOSE

No study has been conducted to compare the clinicians' prediction of survival (CPS) with Palliative Prognostic Scores (PaP) across countries. We aimed to compare the performance of the CPS in PaP (PaP-CPS), the PaP without the CPS, and the PaP total scores in patients with advanced cancer in three East Asian countries.

METHODS

We compared the discriminative accuracy of the three predictive models (the PaP-CPS [the score of the categorical CPS of PaP], the PaP without the CPS [sum of the scores of only the objective variables of PaP], and the PaP total score) in patients admitted to palliative care units (PCUs) in Japan, Korea, and Taiwan. We calculated the area under the receiver operating characteristic curve (AUROC) for 30-day survival to compare the discriminative accuracy of these three models.

RESULTS

We analyzed 2,072 patients from three countries. The AUROC for the PaP total scores was 0.84 in patients in Japan, 0.76 in Korea, and 0.79 in Taiwan. The AUROC of the PaP-CPS was 0.82 in patients in Japan, 0.75 in Korea, and 0.78 in Taiwan. The AUROC of the PaP without the CPS was 0.75 in patients in Japan, 0.66 in Korea, and 0.67 in Taiwan.

CONCLUSION

The PaP total scores and the PaP-CPS consistently showed similar discriminative accuracy in predicting 30-day survival in patients admitted to PCUs in Japan, Korea, and Taiwan. It may be sufficient for experienced clinicians to use the CPS alone for estimating the short-term survival (less than one month) of patients with far-advanced cancer. The PaP may help to improve prognostic confidence and further reduce subjective variations.

Prospective Study Comparing Clinicians' and Cancer Patients' Estimates of Risk of Relapse and Toxicity with Adjuvant Chemotherapy

The aim of this study was to compare physicians' and patients' estimates of risk of relapse and toxicity. A prospective, cross-sectional, multicenter study including 735 patients with cancer and 29 oncologists. Physicians' appraisals of risk of relapse with and without chemotherapy (27.5% and 43.1%) and risk of severe toxicity (12.2%) were more realistic than those of patients (34.6%, 78.5%, and 57.4%, respectively). The greater the risk of recurrence and risk of toxicity estimated, the less physicians expressed satisfaction with SDM. Estimations of risk of relapse and toxicity are important in diagnostic and therapeutic decision-making and can help patients face their situation.

Comparison of the accuracy of clinical prediction of survival and palliative prognostic index for patients with head and neck squamous cell carcinoma in the end-of-life setting

OBJECTIVE

In the end-of-life stage of head and neck squamous cell carcinoma (HNSCC), predicting survival is essential to determine treatment procedure and place of care. Several reports have compared actual survival (AS) and clinical prediction of survival (CPS), a subjective prognostic prediction by attending physicians. However, specific studies focusing on patients with HNSCC are limited. Likewise, a comparison of the accuracy of CPS and palliative prognostic index (PPI), a prognostic tool using subjective assessment, has not been sufficiently investigated. This study aimed to clarify the correlation between AS and CPS/PPI and compare the accuracy of CPS and PPI in end-stage HNSCC.

METHODS

This retrospective study included patients with HNSCC in the end-of-life setting. Patients were recruited from the National Hospital Organization Shikoku Cancer Center between April 2011 and March 2019. Data on basic demography and clinical parameters when patients decided to start end-of-life care at the head and neck oncology division were collected. We examined the correlation between AS and CPS using Spearman's correlation coefficients. The area under the receiver operating characteristic curve of CPS and PPI for 30-day survival prediction were compared for predictive accuracy.

RESULTS

Among 98 eligible patients, 59 patients were enrolled in this study and analyzed. Of the 59 patients, CPS and PPI were calculated for 30 patients, whereas, only the PPI was calculated for 29 patients. The median AS and CPS were 35 (IQR: 9-73) days and 30 (IQR: 7-83) days, respectively. CPS and PPI (30 cases) were moderately correlated (r = 0.72, p<0.01). AS and CPS/PPI (30 cases) were significantly correlated (p<0.01) and showed a strong correlation (r = 0.86 and 0.80, respectively). In the 30-day survival prediction, the AUROCs of CPS and PPI (30 cases) were 0.967 (95%CI: 0.919-1) and 0.884 (95%CI: 0.767-1), respectively. Both CPS and PPI (30 cases) showed high accuracy in predicting the 30-day prognosis, with no significant difference (p = 0.077). The AUROC of PPI (59 cases) was 0.840 (95%CI: 0.711-0.969).

CONCLUSIONS

AS and CPS/PPI showed significant correlations. The high accuracy of CPS may have been influenced by the fact that multiple head and neck cancer specialists at a comprehensive cancer center estimated CPS. Both CPS and PPI showed high prognostic accuracy in predicting 30-day survival. This suggests that PPI is useful in centers among physicians and healthcare workers unfamiliar with head and neck cancer.

Ethical Considerations in Caring for Patients with Advanced Malignancy

Patients with advanced malignancy have decisions to make about next steps that are multifactorial and highly ramified. At each step, they, their loved ones, and their health care providers will attempt to make right decisions and avoid wrong ones. Beyond bare ethical principles, these patients face tensions between what they hope for, what is possible, and what those around them expect and advise. This article uses a case-based approach to explore the balance between prognostication and directive counsel; affective forecasting and decisional regret; hope and the therapeutic misconception; and issues of patient ownership and abandonment at the end of life.

"The surprise questions" using variable time frames in hospitalized patients with advanced cancer

OBJECTIVE

Several studies supported the usefulness of "the surprise question" in terms of 1-year mortality of patients. "The surprise question" requires a "Yes" or "No" answer to the question "Would I be surprised if this patient died in [specific time frame]." However, the 1-year time frame is often too long for advanced cancer patients seen by palliative care personnel. "The surprise question" with shorter time frames is needed for decision making. We examined the accuracy of "the surprise question" for 7-day, 21-day, and 42-day survival in hospitalized patients admitted to palliative care units (PCUs).

METHOD

This was a prospective multicenter cohort study of 130 adult patients with advanced cancer admitted to 7 hospital-based PCUs in South Korea. The accuracy of "the surprise question" was compared with that of the temporal question for clinician's prediction of survival.

RESULTS

We analyzed 130 inpatients who died in PCUs during the study period. The median survival was 21.0 days. The sensitivity, specificity, and overall accuracy for the 7-day "the surprise question" were 46.7, 88.7, and 83.9%, respectively. The sensitivity, specificity, and overall accuracy for the 7-day temporal question were 6.7, 98.3, and 87.7%, respectively. The c-indices of the 7-day "the surprise question" and 7-day temporal question were 0.662 (95% CI: 0.539-0.785) and 0.521 (95% CI: 0.464-0.579), respectively. The c-indices of the 42-day "the surprise question" and 42-day temporal question were 0.554 (95% CI: 0.509-0.599) and 0.616 (95% CI: 0.569-0.663), respectively.

SIGNIFICANCE OF RESULTS

Surprisingly, "the surprise questions" and temporal questions had similar accuracies. The high specificities for the 7-day "the surprise question" and 7- and 21-day temporal question suggest they may be useful to rule in death if positive.

Accuracy of the Palliative Prognostic Score With or Without Clinicians' Prediction of Survival in Patients With Far Advanced Cancer

CONTEXT

Previous studies suggest that clinicians' prediction of survival (CPS) may have reduced the accuracy of objective indicators for prognostication in palliative care.

OBJECTIVES

We aimed to examine the accuracy of CPS alone, compared to the original Palliative Prognostic Score (PaP), and five clinical/laboratory variables of the PaP in patients with far advanced cancer.

METHODS

We compared the discriminative accuracy of three prediction models (the PaP-CPS [the score of the categorical CPS of PaP], PaP without CPS [sum of the scores of only the objective variables of PaP], and PaP total score) across 3 settings: inpatient palliative care consultation team, palliative care unit, and home palliative care. We computed the area under receiver operating characteristic curve (AUROC) for 30-day survival and concordance index (C-index) to compare the discriminative accuracy of these three models.

RESULTS

We included a total of 1534 subjects with median survival of 34.0 days. The AUROC and C-index in the three settings were 0.816-0.896 and 0.732-0.799 for the PaP total score, 0.808-0.884 and 0.713-0.782 for the PaP-CPS, and 0.726-0.815 and 0.672-0.728 for the PaP without CPS, respectively. The PaP total score and PaP-CPS showed similar AUROCs and C-indices across the three settings. The PaP total score had significantly higher AUROCs and C-indices than the PaP without CPS across the three settings.

CONCLUSION

Overall, the PaP total score, PaP-CPS, and PaP without CPS showed good discriminative performances. However, the PaP total score and PaP-CPS were significantly more accurate than the PaP without CPS.

Breast and Lung Effusion Survival Score Models: Improving Survival Prediction in Patients With Malignant Pleural Effusion and Metastasis

BACKGROUND

Evidence-based guidelines recommend management strategies for malignant pleural effusions (MPEs) based on life expectancy. Existent risk-prediction rules do not provide precise individualized survival estimates.

RESEARCH QUESTION

Can a newly developed continuous risk-prediction survival model for patients with MPE and known metastatic disease provide precise survival estimates?

STUDY DESIGN AND METHODS

Single-center retrospective cohort study of patients with proven malignancy, pleural effusion, and known metastatic disease undergoing thoracentesis from 2014 through 2017. The outcome was time from thoracentesis to death. Risk factors were identified using Cox proportional hazards models. Effect-measure modification (EMM) was tested using the Mantel-Cox test and was addressed by using disease-specific models (DSMs) or interaction terms. Three DSMs and a combined model using interactions were generated. Discrimination was evaluated using Harrell's C-statistic. Calibration was assessed by observed-minus-predicted probability graphs at specific time points. Models were validated using patients treated from 2010 through 2013. Using LENT (pleural fluid lactate dehydrogenase, Eastern Cooperative Oncology Group performance score, neutrophil-to-lymphocyte ratio and tumor type) variables, we generated both discrete (LENT-D) and continuous (LENT-C) models, assessing discrete vs continuous predictors' performances.

RESULTS

The development and validation cohort included 562 and 727 patients, respectively. The Mantel-Cox test demonstrated interactions between cancer type and neutrophil to lymphocyte ratio (P < .0001), pleural fluid lactate dehydrogenase (P = .029), and bilateral effusion (P = .002). DSMs for lung, breast, and hematologic malignancies showed C-statistics of 0.72, 0.72, and 0.62, respectively; the combined model's C-statistics was 0.67. LENT-D (C-statistic, 0.60) and LENT-C (C-statistic, 0.65) models underperformed.

INTERPRETATION

EMM is present between cancer type and other predictors; thus, DSMs outperformed the models that failed to account for this. Discrete risk-prediction models lacked enough precision to be useful for individual-level predictions.

Adoption of Immune Checkpoint Inhibitors and Patterns of Care at the End of Life

PURPOSE

As immune checkpoint inhibitors (ICIs) have transformed the care of patients with cancer, it is unclear whether treatment at the end of life (EOL) has changed. Because aggressive therapy at the EOL is associated with increased costs and patient distress, we explored the association between the Food and Drug Administration (FDA) approvals of ICIs and treatment patterns at the EOL.

METHODS

We conducted a retrospective, observational study using patient-level data from a nationwide electronic health record-derived database. Patients had advanced melanoma, non-small-cell lung cancer (NSCLC; cancer types with an ICI indication), or microsatellite stable (MSS) colon cancer (a cancer type without an ICI indication) and died between 2013 and 2017. We calculated annual proportions of decedents who received systemic cancer therapy in the final 30 days of life, using logistic regression to model the association between the post-ICI FDA approval time and use of systemic therapy at the EOL, adjusting for patient characteristics. We assessed the use of chemotherapy or targeted/biologic therapies at the EOL, before and after FDA approval of ICIs using Pearson chi-square test.

RESULTS

There was an increase in use of EOL systemic cancer therapy in the post-ICI approval period for both melanoma (33.9% to 43.2%; P < .001) and NSCLC (37.4% to 40.3%; P < .001), with no significant change in use of systemic therapy in MSS colon cancer. After FDA approval of ICIs, patients with NSCLC and melanoma had a decrease in the use of chemotherapy, with a concomitant increase in use of ICIs at the EOL.

CONCLUSION

The adoption of ICIs was associated with a substantive increase in the use of systemic therapy at the EOL in melanoma and a smaller yet significant increase in NSCLC.

Impact of Prognostic Nutritional Index on Terminal Cancer Patients

BACKGROUND

In terminal cancer patients (TCPs), one of the most important things is to define the survival to help the main responsible physicians, patients, and main caregivers make decisions, set goals, and work across the end-of-life strategies.

PATIENTS AND METHODS

We retrospectively reviewed the medical files of TCPs, who died during September 2011 and December 2017, to recognize the correlation between prognostic nutritional indices (PNIs) and survival in those subtypes of patients. The receiver operating characteristic (ROC) curve was used to identify the cutoff value of PNI.

RESULTS

A total of 858 TCPs were eligible and included, the median age was 62 years (range: 18-107). The most common primary cancer sites were colorectal cancer in 151 patients (17.6%), hepatobiliary in 129 (15%), lung cancer in 115 (13.4%), breast cancer in 114 (13.3%), and genitourinary in 80 (9.3%). The mean value of PNI for all cancer types was 32.9 ± 6.7. The values showed different levels across cancer types. For patients who lived >2 weeks, PNI was 36.7 compared with that who died within 2 weeks was 29.3, which was a statistically significant (P < 0.001). By the ROC curve, the cutoff value of PNI was 32.3 and area under the curve was 0.888. The sensitivity, specificity, positive predictive value, and negative predictive value were 91.28% (95% confidence interval [CI]: 88.2-93.8), 71.09% (95% CI: 66.5-75.4), 76.5% (95% CI: 73.7-79.2), and 88.8% (95% CI: 85.3-91.5), respectively.

CONCLUSION

The PNI is an easy and an applicable biomarker to estimate life expectancy in TCPs.

Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites

BACKGROUND

Automated systems that use machine learning to estimate a patient's risk of death are being developed to influence care. There remains sparse transparent reporting of model generalizability in different subpopulations especially for implemented systems.

METHODS

A prognostic study included adult admissions at a multi-site, academic medical center between 2015 and 2017. A predictive model for all-cause mortality (including initiation of hospice care) within 60 days of admission was developed. Model generalizability is assessed in temporal validation in the context of potential demographic bias. A subsequent prospective cohort study was conducted at the same sites between October 2018 and June 2019. Model performance during prospective validation was quantified with areas under the receiver operating characteristic and precision recall curves stratified by site. Prospective results include timeliness, positive predictive value, and the number of actionable predictions.

RESULTS

Three years of development data included 128,941 inpatient admissions (94,733 unique patients) across sites where patients are mostly white (61%) and female (60%) and 4.2% led to death within 60 days. A random forest model incorporating 9614 predictors produced areas under the receiver operating characteristic and precision recall curves of 87.2 (95% CI, 86.1-88.2) and 28.0 (95% CI, 25.0-31.0) in temporal validation. Performance marginally diverges within sites as the patient mix shifts from development to validation (patients of one site increases from 10 to 38%). Applied prospectively for nine months, 41,728 predictions were generated in real-time (median [IQR], 1.3 [0.9, 32] minutes). An operating criterion of 75% positive predictive value identified 104 predictions at very high risk (0.25%) where 65% (50 from 77 well-timed predictions) led to death within 60 days.

CONCLUSION

Temporal validation demonstrates good model discrimination for 60-day mortality. Slight performance variations are observed across demographic subpopulations. The model was implemented prospectively and successfully produced meaningful estimates of risk within minutes of admission.

How palliative care professionals deal with predicting life expectancy at the end of life: predictors and accuracy

PURPOSE

To assess the accuracy of hospice staff in predicting survival of subjects admitted to hospice, exploring the factors considered most helpful by the hospice staff to accurately predict survival.

METHODS

Five physicians and 11 nurses were asked to predict survival at admission of 827 patients. Actual and predicted survival times were divided into ≤ 1 week, 2-3 weeks, 4-8 weeks, and ≥ 2 months and the accuracy of the estimates was calculated. The staff members were each asked to score 17 clinical variables that guided them in predicting survival and we analyzed how these variables impacted the accuracy.

RESULTS

Physicians' and nurses' accuracy of survival of the patients was 46% and 40% respectively. Survival was underestimated in 20% and 12% and overestimated in 34% and 48% of subjects. Both physicians and nurses considered metastases, comorbidities, dyspnea, disability, tumor site, neurological symptoms, and confusion very important in predicting patients' survival with nurses assigning more importance to intestinal symptoms and pain too. All these factors, with the addition of cough and/or bronchial secretions, were associated with physicians' greater accuracy. In the multivariable models, intestinal symptoms and confusion continued to be associated with greater predictive accuracy. No factors appreciably raised nurses' accuracy.

CONCLUSIONS

Some clinical symptoms rated as relevant by the hospice staff could be important for predicting survival. However, only intestinal symptoms and confusion significantly improved the accuracy of physicians' predictions, despite the high prevalence of overestimated survival.

Acute palliative care unit-initiated interventions for advanced cancer patients at the end of life: prediction of impending death based on Glasgow Prognostic Score

PURPOSE

Unexpected death occurred in an unexpectedly high proportion of advanced cancer patients in the acute palliative care unit (APCU) setting and associated with fewer signs of impending death. Recognition of patients at high risk of approaching death, especially immediately after admitting APCU among clinicians, can improve the end-of-life trajectory. Our objective was accurate prognostication within a few days of admission.

METHODS

Patients admitted to an APCU of the NTT Medical Center Tokyo, Tokyo, Japan, between April 2009 and December 2016 were retrospectively examined. The Glasgow Prognostic Score (GPS) was optimized with concomitant neutrophilia, lymphocytopenia, thrombocytopenia, anemia, and monocytosis. Kaplan-Meier survival curves were estimated, and independent predictors for 3-day mortality were identified using univariate and multivariate analyses. The sensitivity, specificity, and likelihood ratios (LRs) associated with imminent death were also assessed.

RESULTS

Nine hundred ninety-one patients were included; 52.9% was male. The median age was 72 years. The median survival was 13 days (IQ range 6 to 26), and 11.7% died within 3 days of admission. Significant difference in survival with a GPS of 2 was observed in GPS optimized with concomitant thrombocytopenia, and it was the only significant predictor associated with 3-day mortality (p = 0.004), which had high specificity (> 95%) and high positive LR (> 5).

CONCLUSION

The prognostic value of the GPS was enhanced by adding thrombocytopenia. The concurrent use of the GPS and platelet count improved the prognostication of limited time of survival and could assist in the personal and clinical decisions for advanced cancer patients.

Estimating real-world performance of a predictive model: a case-study in predicting mortality

OBJECTIVE

One primary consideration when developing predictive models is downstream effects on future model performance. We conduct experiments to quantify the effects of experimental design choices, namely cohort selection and internal validation methods, on (estimated) real-world model performance.

MATERIALS AND METHODS

Four years of hospitalizations are used to develop a 1-year mortality prediction model (composite of death or initiation of hospice care). Two common methods to select appropriate patient visits from their encounter history (backwards-from-outcome and forwards-from-admission) are combined with 2 testing cohorts (random and temporal validation). Two models are trained under otherwise identical conditions, and their performances compared. Operating thresholds are selected in each test set and applied to a "real-world" cohort of labeled admissions from another, unused year.

RESULTS

Backwards-from-outcome cohort selection retains 25% of candidate admissions (n = 23 579), whereas forwards-from-admission selection includes many more (n = 92 148). Both selection methods produce similar performances when applied to a random test set. However, when applied to the temporally defined "real-world" set, forwards-from-admission yields higher areas under the ROC and precision recall curves (88.3% and 56.5% vs. 83.2% and 41.6%).

DISCUSSION

A backwards-from-outcome experiment manipulates raw training data, simplifying the experiment. This manipulated data no longer resembles real-world data, resulting in optimistic estimates of test set performance, especially at high precision. In contrast, a forwards-from-admission experiment with a temporally separated test set consistently and conservatively estimates real-world performance.

CONCLUSION

Experimental design choices impose bias upon selected cohorts. A forwards-from-admission experiment, validated temporally, can conservatively estimate real-world performance.

LAY SUMMARY

The routine care of patients stands to benefit greatly from assistive technologies, including data-driven risk assessment. Already, many different machine learning and artificial intelligence applications are being developed from complex electronic health record data. To overcome challenges that arise from such data, researchers often start with simple experimental approaches to test their work. One key component is how patients (and their healthcare visits) are selected for the study from the pool of all patients seen. Another is how the group of patients used to create the risk estimator differs from the group used to evaluate how well it works. These choices complicate how the experimental setting compares to the real-world application to patients. For example, different selection approaches that depend on each patient's future outcome can simplify the experiment but are impractical upon implementation as these data are unavailable. We show that this kind of "backwards" experiment optimistically estimates how well the model performs. Instead, our results advocate for experiments that select patients in a "forwards" manner and "temporal" validation that approximates training on past data and implementing on future data. More robust results help gauge the clinical utility of recent works and aid decision-making before implementation into practice.

Prognosticating for Adult Patients With Advanced Incurable Cancer: a Needed Oncologist Skill

Patients with advanced cancer and their families commonly seek information about prognosis to aid decision-making in medical (e.g. surrounding treatment), psychological (e.g. saying goodbye), and social (e.g. getting affairs in order) domains. Oncologists therefore have a responsibility to identify and address these requests by formulating and sensitively communicating information about prognosis. Current evidence suggests that clinician predictions are correlated with actual survival but tend to be overestimations. In an attempt to cultivate prognostic skills, it is recommended that clinicians practice formulating and recording subjective estimates of prognosis in advanced cancer patient’s medical notes. When possible, a multi-professional prognostic estimate should be sought as these may be more accurate than individual predictions alone. Clinicians may consider auditing the accuracy of their predictions periodically and using feedback from this process to improve their prognostic skills.

Clinicians may also consider using validated prognostic tools to complement their clinical judgements. However, there is currently only limited evidence about the comparative accuracy of different prognostic tools or the extent to which these measures are superior to clinical judgement. Oncologists and palliative care physicians should ensure that they receive adequate training in advanced communication skills, which builds upon their pre-existing skills, to sensitively deliver information on prognosis. In particular, clinicians should acknowledge their own prognostic uncertainty and should emphasise the supportive care that can continue to be provided after stopping cancer-directed therapies.

Collapse of Fluid Balance and Association with Survival in Patients with Advanced Cancer Admitted to a Palliative Care Unit: Preliminary Findings

Background: Few studies have investigated water balance as a predictor of survival in cancer patients in the last days of life. Objective: To examine the association between extracellular water (ECW), intracellular water (ICW), ratio of ECW to ICW (ECW/ICW), and survival in nonedematous and edematous patients with advanced cancer admitted to a palliative care unit. Design: A prospective observational study. Setting/Subjects: Patients with advanced cancer admitted to a palliative care unit. Measurements: Upon enrollment, bioelectrical impedance analysis was used to assess ECW, ICW, and body composition. We conducted time-to-event analyses using the Kaplan-Meier method, log-rank test, and univariate and multivariate Cox regression analyses. Results: A total of 190 of 204 patients who participated in this study had ICW and ECW measures available for analysis. The median survival was 10 days (95% confidence interval [CI] 9-12) days. The median ECW, ICW, and ECW/ICW were 18.9 L, 19.1 L, and 1.0 for 72 nonedematous patients, and 21.9 L, 20.1 L, and 1.1 for 118 edematous patients, respectively. In univariate Cox regression analysis, ICW ≤20 L was associated with a shorter survival in the nonedematous patients (hazard ratio [HR] 1.92, 95% CI 1.10-3.34, p = 0.02) and a longer survival in the edematous patients (HR 0.61, 95% CI 0.41-0.90, p = 0.01). In multivariable analysis, ICW (≤20 L vs. >20 L) remained an independent prognostic factor in edematous patients (HR 0.64, 95% CI 0.43-0.95, p = 0.03). Conclusions: Greater ICW was an independent predictor of poorer survival in cancer patients with edema in the last days of life.

Association of Emergency Clinicians' Assessment of Mortality Risk With Actual 1-Month Mortality Among Older Adults Admitted to the Hospital

IMPORTANCE

The accuracy of mortality assessment by emergency clinicians is unknown and may affect subsequent medical decision-making.

OBJECTIVE

To determine the association of the question, "Would you be surprised if your patient died in the next one month?" (known as the surprise question) asked of emergency clinicians with actual 1-month mortality among undifferentiated older adults who visited the emergency department (ED).

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study at a single academic medical center in Portland, Maine, included consecutive patients 65 years or older who received care in the ED and were subsequently admitted to the hospital from January 1, 2014, to December 31, 2015. Data analyses were conducted from January 2018 to March 2019.

EXPOSURES

Treating emergency clinicians were required to answer the surprise question, "Would you be surprised if your patient died in the next one month?" in the electronic medical record when placing a bed request for all patients who were being admitted to the hospital.

MAIN OUTCOMES AND MEASURES

The primary outcome was mortality at 1 month, assessed from the National Death Index. The secondary outcomes included accuracies of responses by both emergency clinicians and admitting internal medicine clinicians to the surprise question in identifying older patients with high 6-month and 12-month mortality.

RESULTS

The full cohort included 10 737 older adults (mean [SD] age, 75.9 [8.8] years; 5532 [52%] women; 10 157 [94.6%] white) in 16 223 visits treated in the ED and admitted to the hospital. There were 5132 patients (31.6%) with a Charlson Comorbidity Index score of 2 or more. Mortality rates were 8.3% at 1 month, 17.2% at 6 months, and 22.5% at 12 months. Emergency clinicians stated that they would not be surprised if the patient died in the next month for 2104 patients (19.6%). In multivariable analysis controlling for age, sex, race, admission diagnosis, and comorbid conditions, the odds of death at 1 month were higher in patients for whom clinicians answered that they would not be surprised if the patient died in the next 1 month compared with patients for whom clinicians answered that they would be surprised if the patient died in the next 1 month (odds ratio, 2.4 [95% CI, 2.2-2.7]; P < .001). However, the diagnostic test characteristics of the surprise question were poor (sensitivity, 20%; specificity, 93%; positive predictive value, 43%; negative predictive value, 82%; accuracy, 78%; area under the receiver operating curve of the multivariable model, 0.73 [95% CI, 0.72-0.74; P < .001]).

CONCLUSIONS AND RELEVANCE

This study found that asking the surprise question of emergency clinicians may be a valuable tool to identify older patients in the ED with a high risk of 1-month mortality. The effect of implementing the surprise question to improve population-level health care for older adults in the ED who are seriously ill remains to be seen.

mHOMR: a feasibility study of an automated system for identifying inpatients having an elevated risk of 1-year mortality

OBJECTIVE

The need for clinical staff to reliably identify patients with a shortened life expectancy is an obstacle to improving palliative and end-of-life care. We developed and evaluated the feasibility of an automated tool to identify patients with a high risk of death in the next year to prompt treating physicians to consider a palliative approach and reduce the identification burden faced by clinical staff.

METHODS

Two-phase feasibility study conducted at two quaternary healthcare facilities in Toronto, Canada. We modified the Hospitalised-patient One-year Mortality Risk (HOMR) score, which identifies patients having an elevated 1-year mortality risk, to use only data available at the time of admission. An application prompted the admitting team when patients had an elevated mortality risk and suggested a palliative approach. The incidences of goals of care discussions and/or palliative care consultation were abstracted from medical records.

RESULTS

Our model (C-statistic=0.89) was found to be similarly accurate to the original HOMR score and identified 15.8% and 12.2% of admitted patients at Sites 1 and 2, respectively. Of 400 patients included, the most common indications for admission included a frailty condition (219, 55%), chronic organ failure (91, 23%) and cancer (78, 20%). At Site 1 (integrated notification), patients with the notification were significantly more likely to have a discussion about goals of care and/or palliative care consultation (35% vs 20%, p = 0.016). At Site 2 (electronic mail), there was no significant difference (45% vs 53%, p = 0.322).

CONCLUSIONS

Our application is an accurate, feasible and timely identification tool for patients at elevated risk of death in the next year and may be effective for improving palliative and end-of-life care.

Nomogram-based parameters to predict overall survival in a real-world advanced cancer population undergoing palliative care

Background

Although palliative care has been accepted throughout the cancer trajectory, accurate survival prediction for advanced cancer patients is still a challenge. The aim of this study is to identify pre-palliative care predictors and develop a prognostic nomogram for overall survival (OS) in mixed advanced cancer patients.

Methods

A total of 378 consecutive advanced cancer patients were retrospectively recruited from July 2013 to October 2015 in one palliative care unit in China. Twenty-three clinical and laboratory characters were collected for analysis. Prognostic factors were identified to construct a nomogram in a training cohort (n = 247) and validated in a testing cohort (n = 131) from the setting.

Results

The median survival time was 48.0 (95% CI: 38.1–57.9) days for the training cohort and 52.0 (95% CI: 34.6–69.3) days for the validation cohort. Among pre-palliative care factors, sex, age, tumor stage, Karnofsky performance status, neutrophil count, hemoglobin, lactate dehydrogenase, albumin, uric acid, and cystatin-C were identified as independent prognostic factors for OS. Based on the 10 factors, an easily obtained nomogram predicting 90-day probability of mortality was developed. The predictive nomogram had good discrimination and calibration, with a high C-index of 0.76 (95% CI: 0.73–0.80) in the development set. The strong discriminative ability was externally conformed in the validation cohort with a C-index of 0.75.

Conclusions

A validated prognostic nomogram has been developed to quantify the risk of mortality for advanced cancer patients undergoing palliative care. This tool may be useful in optimizing therapeutic approaches and preparing for clinical courses individually.

Electronic supplementary material

The online version of this article (10.1186/s12904-019-0432-7) contains supplementary material, which is available to authorized users.

Intensity of Cancer Care Near the End of Life at a Tertiary Care Cancer Center in Jordan

CONTEXT

Chemotherapy use in the last month of life is an indicator of poor quality of end-of-life care.

OBJECTIVES

We assessed the frequency of chemotherapy use at the end of life at our comprehensive cancer center in Jordan and identified the factors associated with chemotherapy use.

METHODS

We conducted a retrospective chart review to examine the use of chemotherapy in the last 30 days and 14 days of life in consecutive adult patients with cancer seen at King Hussein Cancer Center (KHCC) who died between January 1, 2010, and December 31, 2012. We collected data on patient and disease characteristics, palliative care referral, and end-of-life care outcome indicators.

RESULTS

Among the 1714 decedents, 310 (18.1%) had chemotherapy use in the last 30 days and 142 (8.3%) in the last 14 days of life. Over half (910; 53.1%) had a palliative care referral. Chemotherapy use in the last 30 and 14 days of life were associated with younger age (odds ratio [OR] 0.99/yr, P = 0.01, and OR 0.99/yr, P = 0.01, respectively) and hematological malignances (OR 1.98, P < 0.001, and OR 2.85, P < 0.001, respectively). Palliative care referral was significantly associated with decreased use of chemotherapy in the last 30 (OR 0.30, P < 0.001) and 14 (OR 0.15, P < 0.001) days of life.

CONCLUSIONS

A sizable minority of patients with cancer at KHCC received chemotherapy at the end of life. Younger patients and those with hematological malignancies were more likely to receive chemotherapy, whereas those referred to palliative care were significantly less likely to receive chemotherapy at the end of life.

Prognostication in advanced cancer: update and directions for future research

The objective of this review is to provide an update on prognostication in patients with advanced cancer and to discuss future directions for research in this field. Accurate prognostication of survival for patients with advanced cancer is vital, as patient life expectancy informs many important personal and clinical decisions. The most common prognostic approach is clinician prediction of survival (CPS) using temporal, surprise, or probabilistic questions. The surprise and probabilistic questions may be more accurate than the temporal approach, partly by limiting the time frame of prediction. Prognostic models such as the Glasgow Prognostic Score (GPS), Palliative Performance Scale (PPS), Palliative Prognostic Score (PaP), Palliative Prognostic Index (PPI), or Prognosis in Palliative Care Study (PiPS) predictor model may augment CPS. However, care must be taken to select the appropriate tool since prognostic accuracy varies by patient population, setting, and time frame of prediction. In addition to life expectancy, patients and caregivers often desire that expected treatment outcomes and bodily changes be communicated to them in a sensible manner at an appropriate time. We propose the following 10 major themes for future prognostication research: (1) enhancing prognostic accuracy, (2) improving reliability and reproducibility of prognosis, (3) identifying the appropriate prognostic tool for a given setting, (4) predicting the risks and benefits of cancer therapies, (5) predicting survival for pediatric populations, (6) translating prognostic knowledge into practice, (7) understanding the impact of prognostic uncertainty, (8) communicating prognosis, (9) clarifying outcomes associated with delivery of prognostic information, and (10) standardizing prognostic terminology.

Adding a Wider Range and "Hope for the Best, and Prepare for the Worst" Statement: Preferences of Patients with Cancer for Prognostic Communication

INTRODUCTION

Although various phrases to communicate prognoses based on a certain concept have been proposed, no study has systematically investigated preferences of patients with cancer for actual phrases. We investigated whether phrases with a wider range and additional "hope for the best, and prepare for the worst" (hope/prepare) statement would be more preferable and explored variables associated with patients' preferences.

MATERIALS AND METHODS

In a cross-sectional survey, 412 outpatients with cancer self-assessed their preferences for 13 phrases conveying prognostic information (e.g., phrases with or without median, typical range, and/or best/worst cases, and those with or without a hope/prepare statement) on a 6-point scale (1 = not at all preferable; 6 = very preferable). We evaluated demographic data and the Coping Inventory for Stressful Situations and conducted multivariate regression analysis.

RESULTS

Regarding phrases with various ranges, the one including the median, typical range, and best/worst cases was more preferable (mean ± SD, 3.8 ± 1.3; 95% confidence interval [CI], 3.6-3.9) than the one with the median and typical range (3.4 ± 1.2; 3.3-3.6) or the one with only the median (3.2 ± 1.3; 3.1-3.3). Concerning the hope/prepare statement, the phrase including the median, typical range, uncertainty, and hope/prepare statement was more preferable (3.8 ± 1.4; 3.7-3.9) than the one without the statement (3.5 ± 1.2; 3.4-3.6). In multivariate analyses, task-oriented coping was significantly correlated with preferences for phrases with explicit information.

CONCLUSION

Overall, phrases with a wider range and the hope/prepare statement were preferable to those without them. When patients with cancer ask about prognoses, especially those with task-oriented coping, clinicians may provide explicit information with a wider range and the hope/prepare statement.

IMPLICATIONS FOR PRACTICE

Discussing prognoses with patients with advanced cancer is among the most important conversations for clinicians. In this cross-sectional survey to systematically investigate preferences of 412 patients with cancer for phrases conveying prognostic information, phrases with the median, typical range, and best/worst cases and those with the "hope for the best and prepare for the worst" (hope/prepare) statement were the most preferred. When patients with cancer ask about prognoses, clinicians may provide explicit information with a wider range and include the hope/prepare statement.

Reduced Clearance of Phenobarbital in Advanced Cancer Patients near the End of Life

BACKGROUND AND OBJECTIVES

Little is known about the pharmacokinetics of phenobarbital in terminally ill cancer patients. We investigated whether phenobarbital clearance alters depending on the length of survival.

METHODS

We retrospectively reviewed the clinical, laboratory, and therapeutic drug monitoring (TDM) records of patients who received parenteral or oral phenobarbital for 21 consecutive days or longer between 2000 and 2016. Patients were divided into non-cancer and cancer groups. Cancer patients were further stratified according to the survival interval after TDM: those who survived > 3 months were classified as long-surviving and the remainders short-surviving cancer patients. Phenobarbital clearance (CL_PB) was calculated at steady state. Multiple comparisons of median CL_PB were conducted among the three groups.

RESULTS

Data were collected from 44 non-cancer patients and 34 cancer patients comprising 24 long-surviving and 10 short-surviving cancer patients. Among 10 short-surviving cancer patients, 4 had hepatic metastasis. Median CL_PB (range) in short-surviving cancer patients [0.076 (0.057‒0.114) L/kg/day] was significantly (p < 0.05) lower than that in non-cancer patients [0.105 (0.060‒0.226) L/kg/day] and in long-surviving cancer patients [0.100 (0.082‒0.149) L/kg/day].

CONCLUSION

Terminally ill patients with advanced cancer may have reduced CL_PB, thereby TDM is recommended for these patients particularly near the end of life.

Adequate, questionable, and inadequate drug prescribing for older adults at the end of life: a European expert consensus

Background

Clinical guidance is needed to initiate, continue, and discontinue drug treatments near the end of life.

Aim

To identify drugs and drug classes most often adequate, questionable, or inadequate for older people at the end of life.

Design

Delphi consensus survey.

Setting/participants

Forty European experts in geriatrics, clinical pharmacology, and palliative medicine from 10 different countries. Panelists were asked to characterize drug classes as “often adequate,” “questionable,” or “often inadequate” for use in older adults aged 75 years or older with an estimated life expectancy of ≤ 3 months. We distinguished the continuation of a drug class that was previously prescribed from the initiation of a new drug. Consensus was considered achieved for a given drug or drug class if the level of agreement was ≥ 75%.

Results

The expert panel reached consensus on a set of 14 drug classes deemed as “often adequate,” 28 drug classes deemed “questionable,” and 10 drug classes deemed “often inadequate” for continuation during the last 3 months of life. Regarding the initiation of new drug treatments, the panel reached consensus on a set of 10 drug classes deemed “often adequate,” 23 drug classes deemed “questionable,” and 23 drug classes deemed “often inadequate”. Consensus remained unachieved for some very commonly prescribed drug treatments (e.g., proton-pump inhibitors, furosemide, haloperidol, olanzapine, zopiclone, and selective serotonin reuptake inhibitors).

Conclusion

In the absence of high-quality evidence from randomized clinical trials, these consensus-based criteria provide guidance to rationalize drug prescribing for older adults near the end of life.

Electronic supplementary material

The online version of this article (10.1007/s00228-018-2507-4) contains supplementary material, which is available to authorized users.